Accepted: 10 August 2016 DOI: 10.1111/hex.12497
O R I G I N A L R E S E A RC H PA P E R
Examining chronic care patient preferences for involvement in health-care decision making: the case of Parkinson’s disease patients in a patient-centred clinic Natalie Zizzo MSc1,2 | Emily Bell PhD1,3 | Anne-Louise Lafontaine MD, MSc, FRCPC3,4 | Eric Racine PhD1,2,3,5,6 1 Neuroethics Research Unit, Institut de recherches cliniques de Montréal, Montreal, QC, Canada 2
Abstract Background: Patient-centred care is a recommended model of care for Parkinson’s
Division of Experimental Medicine and Biomedical Ethics Unit, McGill University, Montreal, QC, Canada
disease (PD). It aims to provide care that is respectful and responsive to patient prefer-
3
ering how patients want to be involved in their care.
Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada 4 McGill University Health Centre, Montreal, QC, Canada 5
Department of Medicine, Université de Montréal, Montreal, QC, Canada 6
Department of Social and Preventive Medicine, Université de Montréal, Montreal, QC, Canada Correspondence Eric Racine, PhD, Neuroethics Research Unit, Institut de recherches cliniques de Montréal, Montreal, QC, Canada. Email: [email protected]
ences, values and perspectives. Provision of patient-centred care should entail considObjective: To understand the participation preferences of patients with PD from a patient-centred care clinic in health-care decision-making processes. Design, setting and participants: Mixed-methods study with early-stage Parkinson’s disease patients from a patient-centred care clinic. Study involved a modified Autonomy Preference Index survey (N=65) and qualitative, semi-structured in-depth interviews, analysed using thematic qualitative content analysis (N=20, purposefully selected from survey participants). Interviews examined (i) the patient preferences for involvement in health-care decision making; (ii) patient perspectives on the patient– physician relationship; and (iii) patient preferences for communication of information relevant to decision making. Results: Preferences for participation in decision making varied between individuals and also within individuals depending on decision type, relational and contextual factors. Patients had high preferences for communication of information, but with acknowledged limits. The importance of communication in the patient–physician relationship was emphasized. Discussion: Patient preferences for involvement in decision making are dynamic and support shared decision making. Relational autonomy corresponds to how patients envision their participation in decision making. Clinicians may need to assess patient preferences on an on-going basis. Conclusion: Our results highlight the complexities of decision-making processes. Improved understanding of individual preferences could enhance respect for persons and make for patient-centred care that is truly respectful of individual patients’ wants, needs and values. KEYWORDS
bioethics, decision making, Parkinson’s disease, patient preferences, patient-centred care, patient–physician relationship, relational autonomy
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. Health Expectations. 2017;20:655–664. wileyonlinelibrary.com/journal/hex
© 2016 The Authors. Health Expectations | 655 Published by John Wiley & Sons Ltd.
|
Zizzo et al.
656
1 | INTRODUCTION Parkinson’s disease (PD) is a chronic neurodegenerative disease, affecting an estimated 7–10 million individuals worldwide.1 It causes progressive impairments in motor control and often includes psychiatric and cognitive comorbidities in patients as the disease advances. There has been a call for the treatment of PD to be delivered within a patient- centred model of care.2 Although there are many definitions of patient- centred care (PCC), it has been broadly conceived of as “respectful of and responsive to individual patients’ preferences, needs, and values,”3 and it aims to have patient values guide clinical decision making.3 PCC is endorsed by both the Institute of Medicine3 and the Canadian Medical Association4 and has been shown to have instrumental value, with tangible benefits that include better health outcomes.5,6 Furthermore, PCC has been supported from an ethical standpoint;7 it is viewed as an extension of the principles of respect for persons and for autonomy. However, implementing PCC can prove to be challenging, as there is a current lack of understanding on the perspectives, values and preferences of patients with PD for care.8–11 In particular, how patients want to be involved in decision-making processes remains unclear.12–14 In fact, investigations into the variability of patient preferences for the decision-making process show that physicians misjudge patient desire for involvement in decision making.13 This research points to a need to improve the understanding of PD patient preferences for involvement in care. While there has been a great deal of quantitative investigations into these preferences, the qualitative literature is far more sparse15 and patient preferences for involvement in care have not been investigated, to our knowledge, in a chronic care neurodegenerative population. Consequently, we conducted both quantitative surveys and qualitative interviews with PD patients in a PCC clinic to investigate their preferences for involvement in health-care decision-making processes. In our analysis, we draw on the analytic stages of decision making proposed by Charles et al.,16 including (i) information exchange, (ii) deliberation and (iii) decisional control, and consider how patient preferences for involvement may vary with each of these stages. Our results reveal the complexity of decision-making preferences in a PD population and can provide insight for the provision of PCC to other chronic illness and neurodegenerative populations.
2 | METHODS
were selected by maximum variation sampling, a form of purposeful sampling, to maximize the diversity of participants based on age, gender and educational background.18 Interviews were conducted approximately 4–16 weeks after the completion of surveys. The authors’ institutional research ethics boards approved the research protocol, and all participants gave their free and informed written consent.
2.1 | Quantitative methods Participants were surveyed in their preferred language (English or French) using a modified version of the API. The API consists of (i) a six-item decision-making scale, which measures general desire to participate in medical decisions; (ii) an eight-item information scale, which measures desire for medical information; and (iii) five vignettes, which measures desire to participate in medical decisions in specific clinical scenarios. For the decision-making and information scales, summed scores were transformed to a range of 0–100, where a higher score indicates higher preferences for decision-making involvement and for receipt of information, respectively. The vignettes featured in the API are designed to elicit decision-making preferences in the context of different levels of illness severity. The mild (upper respiratory tract illness) and moderate (hypertension) disease vignettes came from the standard API and were kept because of their applicability and relevance. Three novel vignettes were generated to represent the severe disease in the specific context of PD to ensure greater relevance to our participants. The PD-specific vignettes were developed in collaboration with an interdisciplinary PD medical team to feature PD progression (mild worsening of symptoms, moderate worsening of symptoms, new appearance of psychological symptoms). In each vignette, participants indicated their preferred decision-maker for three decisions (decision-making scores: 1 = doctor alone; 2 = mostly the doctor; 3 = the doctor and you; 4 = mostly you; 5 = you alone). For each vignette, the decision-making scores were summed and transformed to a range of 0–10, where a higher score indicated greater desire for involvement in the decision-making process. Descriptive statistics (means, frequencies, range and standard deviation) were calculated for the sample on each scale of the API and for each vignette. The influence of demographic factors (age, gender, level of education) and medical information preferences (information scale of the API) on decision-making preferences as a final outcome measure (decision-making scale of the API) was examined using univariate and multivariable logistic regression analyses. Bivariate relationships between the transformed decision-making preference scores on
The sample population in this study consisted of early-stage PD pa-
the five vignettes were examined using Pearson’s correlation analy-
tients from a PCC movement disorder clinic. Patients who were not
sis. Repeated-measures ANOVA mixed-model approach assessed
proficient in English or French, or who had cognitive deficits based
whether the vignettes had an effect on the final transformed decision-
on validated cognitive tests (Montreal Cognitive Assessment) on file,
making score on this part of the survey. Pre-planned post hoc analysis
were excluded, as these factors could impact their ability to be in-
compared the average decision-making scores on the general medical
volved in decision making. All appropriate candidates, as identified by
vignettes to each of the three PD vignettes. The average decision-
medical staff at the clinic, were approached to complete a modified
making scores of the three PD-specific medical scenarios were also
version of the Autonomy Preference Index (API).17 Survey participants
compared. All statistical analyses were carried out using SAS 9.4 sta-
self-identified whether they were interested in participating in a fol-
tistical software. For all inferential analyses, the probability of type 1
low-up qualitative semi-structured interview. Interview participants
error was a priori fixed at alpha=0.05.
|
657
Zizzo et al.
2.2 | Qualitative methods
to ensure rigour and thoroughness. Upon the completion of coding, the results were reviewed and some nodes were further analysed. The pri-
We aimed to interview approximately 20 patients, as we expected this N
mary author conducted the interviews and coded all interviews; the
was sufficient for theoretical saturation (i.e. the point at which there was
second author systematically reviewed all coding. Disagreements be-
no significant new data). Indeed, this N was consistent with similar quali-
tween the coder and the reviewer were discussed to achieve consen-
11,19,20
tative research,
and an N of 20 yielded sufficiently dense data
sus, and the last author arbitrated outstanding disagreements. Coding
with diverse experiences and perspectives represented. If there was a
was supported by the QSR NVivo 9 qualitative analysis software
partner or another individual who regularly attended clinical appoint-
package. The final key themes for coding were as follows: (i) preferred
ments with the patient, the patient was invited to include this person in
decision-making model (e.g. how should each individual be involved in
the interview as this allowed us to acquire ecologically valuable data (i.e.
decision making?); (ii) qualities of a good patient–physician relationship
a more natural representation of the decision-making process).21
(e.g. general features of a good relationship, important qualities of a
Interviews were semi-structured with open-ended questions cen-
patient and of a physician, values important to care); (iii) PD information
tred on our research aim. We examined (i) patient preferences for in-
preferences (e.g. sources of and desire for information, limits to learning
volvement in health-care decision making; (ii) patient perspectives on
information).
the patient–physician relationship, which is central to health-care de-
Qualitative content is summarized and direct quotes are used to
cision making; and (iii) patient preferences for the communication of
illustrate the perspectives of participants. Some quotes reported in
information. Our questions on participation preferences did not spec-
this study were translated from French to English by the primary au-
ify the types of health-care decisions, which allowed patients to inter-
thor and verified by another bilingual team member (the last author).
pret the question to the types of decisions most representative of their
Participant’s names and identifying details have been removed to
experience. We also inquired about two hypothetical situations: one
protect confidentiality. Patients are identified in text by the letter P
in which there is a conflict between patient and physician and one in
followed by a number that was assigned sequentially as surveys were
which the patient might be excluded from decision making. When pa-
completed. Patients’ partners share the same identifier as the patient
tients’ partners were present, questions were modified to include their
but are differentiated by a prime symbol (e.g. PXX′), and the letter “I”
perspectives.
identifies the interviewer. Some quotes contain minor edits to enhance
Interviews were conducted face-to-face, and were held at the pri-
readability.
mary author’s research institution or at the specialist clinic, according to the patient’s preference. The interviews were conducted in English or French, audio-recorded, transcribed verbatim by an external profes-
3 | RESULTS
sional transcription service and verified by a team member. A technical error resulted in failure to record one interview; in this case, detailed notes were taken immediately after the interview and verified by the participant for their accuracy, and then, these notes were used for analysis. We analysed (“coded”) interview transcripts using thematic quali-
3.1 | Quantitative results 3.1.1 | Participant demographics
tative content analysis.22 An initial coding guide was developed after
Sixty-five patients with PD completed the survey, 27 females (41.5%)
review of transcripts and a team discussion. This coding guide was pi-
and 38 males (58.5%). The age range of participants was 39–85, with
loted on a diversified sample of interviews (N=5, or 25% of total sam-
a mean age of 68. Twenty-one participants (33.9%) had an education
ple). Pilot results led us to revise the coding guide, update coding of
that was equal to or less than a professional college degree, 20 partici-
the initial sample and code the remainder of interviews. The coding
pants (30.8%) had a bachelor’s degree and 24 patients had postgradu-
guide contained definitions and rules for the application of each code
ate education (36.9%).
T A B L E 1 Distribution of responses to statements describing decision-making preferences (% of participants responding)a Strongly disagree Q1: The important medical decisions should be made by your doctor not you
33.9
6.2
23.1
15.4
21.5
Q2: You should go along with your doctor’s advice even if you disagree with it
29.2
16.9
20.0
16.9
16.9
Q3: When hospitalized you should not be making decisions about your own care
32.3
26.2
13.9
7.7
20.0
Q4: You should feel free to make decisions about everyday medical problems
6.2
7.7
23.1
18.5
44.6
Q5: If you were sick, as your illness became worse you would want your doctor to take greater control
9.2
12.3
21.5
26.2
30.8
27.7
16.9
30.8
7.7
16.9
Q6: You should decide how frequently you need a check-up a
Strongly agree
Shaded cells indicate what would be the response aligning with a preference for greatest autonomy in medical decision making.
|
Zizzo et al.
658
T A B L E 2 Mean API score in different vignettes Vignette 1 (cold)
Vignette 2 (blood pressure)
Vignette 3 (routine PD)
Vignette 4 (PD progression)
Vignette 5 (PD-associated emotional distress)
Mean (potential range of 0–10)
5.9 (SD ±1.59)
5.0 (SD ±1.52)
4.4 (SD ±1.39)
4.9 (SD ±1.49)
6.7 (SD ±1.46)
Range
3–9
2–9
2–7
2–7
3–10
3.1.2 | Decision-making preferences
university, graduate) and API information scale score (continuous variable). Listwise deletion was applied for all explanatory variables, result-
The mean decision-making scale score was 62.8±16.6 out of a pos-
ing in the exclusion of one subject from regression analyses due to
sible range of 0–100 (range: 20–97). Distributions of responses to
missing age in the database. Thus, the linear regression models were
statements on the decision-making scale are presented in Table 1. For all questions except Q5 and Q6, the highest percentage of participants chose the answer indicating the most autonomous preference. Responses for questions five and six indicated that most participants desired less autonomy in these scenarios; only two participants preferred high autonomy answers for both of these questions.
3.1.3 | Information preferences The mean information seeking scale score was 87.9±14.9 out of a possible range of 0–100 (range: 28–100). The mode was 100, with 17 participants (26%) scoring the maximum on information preferences.
carried out on 64 participants. Overall, none of the factors reached statistically significant levels in the multivariate or univariable models.
3.2 | Qualitative results 3.2.1 | Participant demographics Twenty PD patient participants were interviewed, 10 males and 10 females. Participants were aged 50–77, with a mean age of 63. Fifteen interviews were conducted in English, and five were conducted in French. The average length of time participants were patients in the specialist clinic was 3 years, with 6 months as the shortest time and 7 years as the longest. Seven patient participants had a professional
3.1.4 | Vignette decision-making preferences Mean decision-making scores for each vignette are presented on a possible range of 1–10 in Table 2. Decision-making scores in vignettes 2 and 3, and vignettes 3 and 4, were moderately correlated (vignettes 2 and 3: r=.50, 95% CI [0.29; 0.66] P=
O R I G I N A L R E S E A RC H PA P E R
Examining chronic care patient preferences for involvement in health-care decision making: the case of Parkinson’s disease patients in a patient-centred clinic Natalie Zizzo MSc1,2 | Emily Bell PhD1,3 | Anne-Louise Lafontaine MD, MSc, FRCPC3,4 | Eric Racine PhD1,2,3,5,6 1 Neuroethics Research Unit, Institut de recherches cliniques de Montréal, Montreal, QC, Canada 2
Abstract Background: Patient-centred care is a recommended model of care for Parkinson’s
Division of Experimental Medicine and Biomedical Ethics Unit, McGill University, Montreal, QC, Canada
disease (PD). It aims to provide care that is respectful and responsive to patient prefer-
3
ering how patients want to be involved in their care.
Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada 4 McGill University Health Centre, Montreal, QC, Canada 5
Department of Medicine, Université de Montréal, Montreal, QC, Canada 6
Department of Social and Preventive Medicine, Université de Montréal, Montreal, QC, Canada Correspondence Eric Racine, PhD, Neuroethics Research Unit, Institut de recherches cliniques de Montréal, Montreal, QC, Canada. Email: [email protected]
ences, values and perspectives. Provision of patient-centred care should entail considObjective: To understand the participation preferences of patients with PD from a patient-centred care clinic in health-care decision-making processes. Design, setting and participants: Mixed-methods study with early-stage Parkinson’s disease patients from a patient-centred care clinic. Study involved a modified Autonomy Preference Index survey (N=65) and qualitative, semi-structured in-depth interviews, analysed using thematic qualitative content analysis (N=20, purposefully selected from survey participants). Interviews examined (i) the patient preferences for involvement in health-care decision making; (ii) patient perspectives on the patient– physician relationship; and (iii) patient preferences for communication of information relevant to decision making. Results: Preferences for participation in decision making varied between individuals and also within individuals depending on decision type, relational and contextual factors. Patients had high preferences for communication of information, but with acknowledged limits. The importance of communication in the patient–physician relationship was emphasized. Discussion: Patient preferences for involvement in decision making are dynamic and support shared decision making. Relational autonomy corresponds to how patients envision their participation in decision making. Clinicians may need to assess patient preferences on an on-going basis. Conclusion: Our results highlight the complexities of decision-making processes. Improved understanding of individual preferences could enhance respect for persons and make for patient-centred care that is truly respectful of individual patients’ wants, needs and values. KEYWORDS
bioethics, decision making, Parkinson’s disease, patient preferences, patient-centred care, patient–physician relationship, relational autonomy
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. Health Expectations. 2017;20:655–664. wileyonlinelibrary.com/journal/hex
© 2016 The Authors. Health Expectations | 655 Published by John Wiley & Sons Ltd.
|
Zizzo et al.
656
1 | INTRODUCTION Parkinson’s disease (PD) is a chronic neurodegenerative disease, affecting an estimated 7–10 million individuals worldwide.1 It causes progressive impairments in motor control and often includes psychiatric and cognitive comorbidities in patients as the disease advances. There has been a call for the treatment of PD to be delivered within a patient- centred model of care.2 Although there are many definitions of patient- centred care (PCC), it has been broadly conceived of as “respectful of and responsive to individual patients’ preferences, needs, and values,”3 and it aims to have patient values guide clinical decision making.3 PCC is endorsed by both the Institute of Medicine3 and the Canadian Medical Association4 and has been shown to have instrumental value, with tangible benefits that include better health outcomes.5,6 Furthermore, PCC has been supported from an ethical standpoint;7 it is viewed as an extension of the principles of respect for persons and for autonomy. However, implementing PCC can prove to be challenging, as there is a current lack of understanding on the perspectives, values and preferences of patients with PD for care.8–11 In particular, how patients want to be involved in decision-making processes remains unclear.12–14 In fact, investigations into the variability of patient preferences for the decision-making process show that physicians misjudge patient desire for involvement in decision making.13 This research points to a need to improve the understanding of PD patient preferences for involvement in care. While there has been a great deal of quantitative investigations into these preferences, the qualitative literature is far more sparse15 and patient preferences for involvement in care have not been investigated, to our knowledge, in a chronic care neurodegenerative population. Consequently, we conducted both quantitative surveys and qualitative interviews with PD patients in a PCC clinic to investigate their preferences for involvement in health-care decision-making processes. In our analysis, we draw on the analytic stages of decision making proposed by Charles et al.,16 including (i) information exchange, (ii) deliberation and (iii) decisional control, and consider how patient preferences for involvement may vary with each of these stages. Our results reveal the complexity of decision-making preferences in a PD population and can provide insight for the provision of PCC to other chronic illness and neurodegenerative populations.
2 | METHODS
were selected by maximum variation sampling, a form of purposeful sampling, to maximize the diversity of participants based on age, gender and educational background.18 Interviews were conducted approximately 4–16 weeks after the completion of surveys. The authors’ institutional research ethics boards approved the research protocol, and all participants gave their free and informed written consent.
2.1 | Quantitative methods Participants were surveyed in their preferred language (English or French) using a modified version of the API. The API consists of (i) a six-item decision-making scale, which measures general desire to participate in medical decisions; (ii) an eight-item information scale, which measures desire for medical information; and (iii) five vignettes, which measures desire to participate in medical decisions in specific clinical scenarios. For the decision-making and information scales, summed scores were transformed to a range of 0–100, where a higher score indicates higher preferences for decision-making involvement and for receipt of information, respectively. The vignettes featured in the API are designed to elicit decision-making preferences in the context of different levels of illness severity. The mild (upper respiratory tract illness) and moderate (hypertension) disease vignettes came from the standard API and were kept because of their applicability and relevance. Three novel vignettes were generated to represent the severe disease in the specific context of PD to ensure greater relevance to our participants. The PD-specific vignettes were developed in collaboration with an interdisciplinary PD medical team to feature PD progression (mild worsening of symptoms, moderate worsening of symptoms, new appearance of psychological symptoms). In each vignette, participants indicated their preferred decision-maker for three decisions (decision-making scores: 1 = doctor alone; 2 = mostly the doctor; 3 = the doctor and you; 4 = mostly you; 5 = you alone). For each vignette, the decision-making scores were summed and transformed to a range of 0–10, where a higher score indicated greater desire for involvement in the decision-making process. Descriptive statistics (means, frequencies, range and standard deviation) were calculated for the sample on each scale of the API and for each vignette. The influence of demographic factors (age, gender, level of education) and medical information preferences (information scale of the API) on decision-making preferences as a final outcome measure (decision-making scale of the API) was examined using univariate and multivariable logistic regression analyses. Bivariate relationships between the transformed decision-making preference scores on
The sample population in this study consisted of early-stage PD pa-
the five vignettes were examined using Pearson’s correlation analy-
tients from a PCC movement disorder clinic. Patients who were not
sis. Repeated-measures ANOVA mixed-model approach assessed
proficient in English or French, or who had cognitive deficits based
whether the vignettes had an effect on the final transformed decision-
on validated cognitive tests (Montreal Cognitive Assessment) on file,
making score on this part of the survey. Pre-planned post hoc analysis
were excluded, as these factors could impact their ability to be in-
compared the average decision-making scores on the general medical
volved in decision making. All appropriate candidates, as identified by
vignettes to each of the three PD vignettes. The average decision-
medical staff at the clinic, were approached to complete a modified
making scores of the three PD-specific medical scenarios were also
version of the Autonomy Preference Index (API).17 Survey participants
compared. All statistical analyses were carried out using SAS 9.4 sta-
self-identified whether they were interested in participating in a fol-
tistical software. For all inferential analyses, the probability of type 1
low-up qualitative semi-structured interview. Interview participants
error was a priori fixed at alpha=0.05.
|
657
Zizzo et al.
2.2 | Qualitative methods
to ensure rigour and thoroughness. Upon the completion of coding, the results were reviewed and some nodes were further analysed. The pri-
We aimed to interview approximately 20 patients, as we expected this N
mary author conducted the interviews and coded all interviews; the
was sufficient for theoretical saturation (i.e. the point at which there was
second author systematically reviewed all coding. Disagreements be-
no significant new data). Indeed, this N was consistent with similar quali-
tween the coder and the reviewer were discussed to achieve consen-
11,19,20
tative research,
and an N of 20 yielded sufficiently dense data
sus, and the last author arbitrated outstanding disagreements. Coding
with diverse experiences and perspectives represented. If there was a
was supported by the QSR NVivo 9 qualitative analysis software
partner or another individual who regularly attended clinical appoint-
package. The final key themes for coding were as follows: (i) preferred
ments with the patient, the patient was invited to include this person in
decision-making model (e.g. how should each individual be involved in
the interview as this allowed us to acquire ecologically valuable data (i.e.
decision making?); (ii) qualities of a good patient–physician relationship
a more natural representation of the decision-making process).21
(e.g. general features of a good relationship, important qualities of a
Interviews were semi-structured with open-ended questions cen-
patient and of a physician, values important to care); (iii) PD information
tred on our research aim. We examined (i) patient preferences for in-
preferences (e.g. sources of and desire for information, limits to learning
volvement in health-care decision making; (ii) patient perspectives on
information).
the patient–physician relationship, which is central to health-care de-
Qualitative content is summarized and direct quotes are used to
cision making; and (iii) patient preferences for the communication of
illustrate the perspectives of participants. Some quotes reported in
information. Our questions on participation preferences did not spec-
this study were translated from French to English by the primary au-
ify the types of health-care decisions, which allowed patients to inter-
thor and verified by another bilingual team member (the last author).
pret the question to the types of decisions most representative of their
Participant’s names and identifying details have been removed to
experience. We also inquired about two hypothetical situations: one
protect confidentiality. Patients are identified in text by the letter P
in which there is a conflict between patient and physician and one in
followed by a number that was assigned sequentially as surveys were
which the patient might be excluded from decision making. When pa-
completed. Patients’ partners share the same identifier as the patient
tients’ partners were present, questions were modified to include their
but are differentiated by a prime symbol (e.g. PXX′), and the letter “I”
perspectives.
identifies the interviewer. Some quotes contain minor edits to enhance
Interviews were conducted face-to-face, and were held at the pri-
readability.
mary author’s research institution or at the specialist clinic, according to the patient’s preference. The interviews were conducted in English or French, audio-recorded, transcribed verbatim by an external profes-
3 | RESULTS
sional transcription service and verified by a team member. A technical error resulted in failure to record one interview; in this case, detailed notes were taken immediately after the interview and verified by the participant for their accuracy, and then, these notes were used for analysis. We analysed (“coded”) interview transcripts using thematic quali-
3.1 | Quantitative results 3.1.1 | Participant demographics
tative content analysis.22 An initial coding guide was developed after
Sixty-five patients with PD completed the survey, 27 females (41.5%)
review of transcripts and a team discussion. This coding guide was pi-
and 38 males (58.5%). The age range of participants was 39–85, with
loted on a diversified sample of interviews (N=5, or 25% of total sam-
a mean age of 68. Twenty-one participants (33.9%) had an education
ple). Pilot results led us to revise the coding guide, update coding of
that was equal to or less than a professional college degree, 20 partici-
the initial sample and code the remainder of interviews. The coding
pants (30.8%) had a bachelor’s degree and 24 patients had postgradu-
guide contained definitions and rules for the application of each code
ate education (36.9%).
T A B L E 1 Distribution of responses to statements describing decision-making preferences (% of participants responding)a Strongly disagree Q1: The important medical decisions should be made by your doctor not you
33.9
6.2
23.1
15.4
21.5
Q2: You should go along with your doctor’s advice even if you disagree with it
29.2
16.9
20.0
16.9
16.9
Q3: When hospitalized you should not be making decisions about your own care
32.3
26.2
13.9
7.7
20.0
Q4: You should feel free to make decisions about everyday medical problems
6.2
7.7
23.1
18.5
44.6
Q5: If you were sick, as your illness became worse you would want your doctor to take greater control
9.2
12.3
21.5
26.2
30.8
27.7
16.9
30.8
7.7
16.9
Q6: You should decide how frequently you need a check-up a
Strongly agree
Shaded cells indicate what would be the response aligning with a preference for greatest autonomy in medical decision making.
|
Zizzo et al.
658
T A B L E 2 Mean API score in different vignettes Vignette 1 (cold)
Vignette 2 (blood pressure)
Vignette 3 (routine PD)
Vignette 4 (PD progression)
Vignette 5 (PD-associated emotional distress)
Mean (potential range of 0–10)
5.9 (SD ±1.59)
5.0 (SD ±1.52)
4.4 (SD ±1.39)
4.9 (SD ±1.49)
6.7 (SD ±1.46)
Range
3–9
2–9
2–7
2–7
3–10
3.1.2 | Decision-making preferences
university, graduate) and API information scale score (continuous variable). Listwise deletion was applied for all explanatory variables, result-
The mean decision-making scale score was 62.8±16.6 out of a pos-
ing in the exclusion of one subject from regression analyses due to
sible range of 0–100 (range: 20–97). Distributions of responses to
missing age in the database. Thus, the linear regression models were
statements on the decision-making scale are presented in Table 1. For all questions except Q5 and Q6, the highest percentage of participants chose the answer indicating the most autonomous preference. Responses for questions five and six indicated that most participants desired less autonomy in these scenarios; only two participants preferred high autonomy answers for both of these questions.
3.1.3 | Information preferences The mean information seeking scale score was 87.9±14.9 out of a possible range of 0–100 (range: 28–100). The mode was 100, with 17 participants (26%) scoring the maximum on information preferences.
carried out on 64 participants. Overall, none of the factors reached statistically significant levels in the multivariate or univariable models.
3.2 | Qualitative results 3.2.1 | Participant demographics Twenty PD patient participants were interviewed, 10 males and 10 females. Participants were aged 50–77, with a mean age of 63. Fifteen interviews were conducted in English, and five were conducted in French. The average length of time participants were patients in the specialist clinic was 3 years, with 6 months as the shortest time and 7 years as the longest. Seven patient participants had a professional
3.1.4 | Vignette decision-making preferences Mean decision-making scores for each vignette are presented on a possible range of 1–10 in Table 2. Decision-making scores in vignettes 2 and 3, and vignettes 3 and 4, were moderately correlated (vignettes 2 and 3: r=.50, 95% CI [0.29; 0.66] P=
